Basic analytical capabilities of the CCR-DEA model
AbstractThe article describes some analytical applications of the basic DEA model – CCR model proposed by Charnes, Cooper and Rhodes . The author presents elementary DEA profiles, terminology, ideas and some traditional ways of determining the optimal technology for inefficient objects and benchmarking and estimating the type and size of returns to scale. The evaluation of input excess and output shortage is also described. In this context, the author suggests an economic interpretation of the optimal solution of the CCR model as a task that consists of creating virtual technology of a given set of objects. The author also presents how to determine the structure of a target and optimal technology and indicates the way of using simplex reports in sensitivity analysis of the solution to the CCR model. All these reflections are illustrated by a real-life DEA problem that concerns bank efficiency.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Wroclaw University of Technology, Institute of Organization and Management in its journal Operations Research and Decisions.
Volume (Year): 1 (2009)
Issue (Month): ()
CCR-DEA; interpretation of CCR model; Optimal technology structure;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
- Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
- Tofallis, C., 1996. "Improving discernment in DEA using profiling," Omega, Elsevier, vol. 24(3), pages 361-364, June.
- Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
- Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Piotr Wawrzynowski).
If references are entirely missing, you can add them using this form.